Hasil untuk "Structural engineering (General)"

Joseph Olasehinde Afolayan, Stephen Adeyemi Alabi, Bilikisu Mojisola Olufowobi

Abstract The current practice in civil engineering is to provide designs with a certain level of safety, which makes it necessary to forecast how a system will perform with minimal or no prior knowledge. These current design methodologies commonly fall short of expectations in unexpected contexts since they are typically only learned via several iterations of trial and error. This study examined the reliability of a typical Howe-type steel roof truss system used for a recently constructed mega-church in one of Nigeria’s main cities. To help the designer determine the expected performance and suitable safety levels for such steel roof truss construction, the design data were applied to the other 11 major cities from the six geopolitical zones in Nigeria. To produce identical policy guidelines to the designer, the dimensional requirements for the roof truss were also reproduced for a span of 12 m, a truss height of 3 m and 28 m, and a height of 5 m in all the zones. For every truss element, a reliability index was developed to measure the structural performance based on the likelihood of failure. The reliability indices were found to be quite sensitive to the size of the steel sections employed. Therefore, as the number of steel sections employed in the design increases, the safety indices, reduce, suggesting an increase in dead loads. Based on the system-level probability of failure of the truss members, contour maps were developed. Therefore, it is advised that the reliability concept be used in the reevaluation of both new and old civil structures.

José Peixoto, Alexis Gonzalez, Janki Bhimani et al.

Programmable caching engines like CacheLib are widely used in production systems to support diverse workloads in multi-tenant environments. CacheLib's design focuses on performance, portability, and configurability, allowing applications to inherit caching improvements with minimal implementation effort. However, its behavior under dynamic and evolving workloads remains largely unexplored. This paper presents an empirical study of CacheLib with multi-tenant settings under dynamic and volatile environments. Our evaluation across multiple CacheLib configurations reveals several limitations that hinder its effectiveness under such environments, including rigid configurations, limited runtime adaptability, lack of quality-of-service support and coordination, which lead to suboptimal performance, inefficient memory usage, and tenant starvation. Based on these findings, we outline future research directions to improve the adaptability, fairness, and programmability of future caching engines.

Kangning Shen, Jingyuan Zhang, Chenxi Sun et al.

Large Language Models (LLMs) have demonstrated significant potential as autonomous software engineering (SWE) agents. Recent work has further explored augmenting these agents with memory mechanisms to support long-horizon reasoning. However, these approaches typically operate at a coarse instance granularity, treating the entire problem-solving episode as the atomic unit of storage and retrieval. We empirically demonstrate that instance-level memory suffers from a fundamental granularity mismatch, resulting in misguided retrieval when tasks with similar surface descriptions require distinct reasoning logic at specific stages. To address this, we propose Structurally Aligned Subtask-Level Memory, a method that aligns memory storage, retrieval, and updating with the agent's functional decomposition. Extensive experiments on SWE-bench Verified demonstrate that our method consistently outperforms both vanilla agents and strong instance-level memory baselines across diverse backbones, improving mean Pass@1 over the vanilla agent by +4.7 pp on average (e.g., +6.8 pp on Gemini 2.5 Pro). Performance gains grow with more interaction steps, showing that leveraging past experience benefits long-horizon reasoning in complex software engineering tasks.

Giulia Angelucci, Edoardo Cecca, Fabrizio Mollaioli

The increasing demand for efficient lateral load-resisting systems in high-rise construction necessitates the investigation of advanced structural solutions. Among many alternatives, outrigger systems are widely acknowledged as effective supplementary schemes for enhancing the strength and stability of tall buildings subjected to lateral loads. This work investigates whether the potential of such systems, well established for regular structures, also remains valid for the complex-shaped geometries that often characterize contemporary tall buildings. Tilted and twisted geometries are explored via the parametric variation of tilt and twist angles. The structural response, both with and without outriggers, is evaluated and compared to that of a regular geometry. The number, location, and relative stiffness of outriggers with respect to the inner core are also systematically varied to provide a comprehensive assessment. To facilitate the extensive parametric analysis, simplified analytical models are employed. Then, a selection of representative geometries are utilized to generate refined three-dimensional numerical models. A comparative survey between these two modeling approaches elucidates the accuracy and limitations of simplified methodologies, while providing insights into the structural behavior of outrigger systems. This work underscores the critical interaction between building configuration, outrigger location, and flexural stiffness in optimizing high-rise structural performance. The results reveal a significant influence of the building’s morphology on the structural response, with major improvements exhibited by regular and tilted configurations. Conversely, twisted geometries can considerably alter global structural behavior depending on their degree of twist, potentially diminishing the outrigger’s efficacy in mitigating lateral displacement and core base moment demands. By providing quantifiable insights into outrigger performance in complex-shaped structures, this research guides a more integrated architectural and structural approach in contemporary high-rise construction, leveraging an efficient simplified modeling framework for preliminary design.

Xinzhi Duan

To evaluate the bonding behavior between ribbed steel bars and ultra-high-performance concrete (UHPC), several pull-out samples were experimentally investigated and presented. The influences of bar diameter and embedment length on the bond failure mode, ultimate bond stress, stress?slip curve and bond stress distribution were investigated. Compared with that of ordinary reinforced concrete, the ultimate bond stress between steel bars and UHPC was increased by 74% under the same conditions. In addition, the bond-slip curve showed a relatively large slope before the ultimate bond stress was reached, and at the same time, the curve showed better ductility after the ultimate bond stress was exceeded. When the sample experiences steel bar yielding or pull-out failure, the bond stress distribution curve exhibits typical multipeak features. As the bar embedment length increased, the bond stress distribution became increasingly heterogeneous, and the increase in the peak number in the bond stress distribution curve reflected this trend. Under appropriate concrete cover thickness, the critical embedment length was between 4d and 6d.

Nassima Naboulsi, Fatima Majid, Taoufik Hachimi et al.

Conductive PLA is an innovative composite material that combines the ecological benefits of polylactic acid, a biodegradable thermoplastic, with electrical conductivity properties. Usually used in additive manufacturing for its ease of printing and low environmental impact, PLA remains an insulator, which limits its applications in the electrical field. To overcome this limitation, conductive fillers such as carbon nanotubes or carbon black are being added, opening the way to new functional uses. This study focuses on a specific composite: carbon black-filled PLA (PLA-CB). This material combines the qualities of traditional PLA with enhanced conductivity thanks to the carbon black particles. To assess its performance, a number of mechanical tests were carried out, including tensile tests on samples manufactured by 3D printing using the FFF process. The study focused in particular on the influence of crosshead speed and the impact of different notch shapes on the material's properties. To analyze the durability of PLA-CB, a probabilistic model based on the two-parameter Weibull distribution was used to assess the risk of failure under different conditions. Reliability curves were also established to better understand the tensile stress and strain at break of the material. This approach could also be applied to other 3D-printed polymers to refine their analytical and numerical modeling.

Pierre-Emmanuel Goffi, Raphaël Tremblay, Bentley Oakes

Successfully engineering interactive industrial DTs is a complex task, especially when implementing services beyond passive monitoring. We present here an experience report on engineering a safety-critical digital twin (DT) for beer fermentation monitoring, which provides continual sampling and reduces manual sampling time by 91%. We document our systematic methodology and practical solutions for implementing bidirectional DTs in industrial environments. This includes our three-phase engineering approach that transforms a passive monitoring system into an interactive Type 2 DT with real-time control capabilities for pressurized systems operating at seven bar. We contribute details of multi-layered safety protocols, hardware-software integration strategies across Arduino controllers and Unity visualization, and real-time synchronization solutions. We document specific engineering challenges and solutions spanning interdisciplinary integration, demonstrating how our use of the constellation reporting framework facilitates cross-domain collaboration. Key findings include the critical importance of safety-first design, simulation-driven development, and progressive implementation strategies. Our work thus provides actionable guidance for practitioners developing DTs requiring bidirectional control in safety-critical applications.

Saba Sanami, Amir G. Aghdam

Reliable aero-engine anomaly detection is crucial for ensuring aircraft safety and operational efficiency. This research explores the application of the Fisher autoencoder as an unsupervised deep learning method for detecting anomalies in aero-engine multivariate sensor data, using a Gaussian mixture as the prior distribution of the latent space. The proposed method aims to minimize the Fisher divergence between the true and the modeled data distribution in order to train an autoencoder that can capture the normal patterns of aero-engine behavior. The Fisher divergence is robust to model uncertainty, meaning it can handle noisy or incomplete data. The Fisher autoencoder also has well-defined latent space regions, which makes it more generalizable and regularized for various types of aero-engines as well as facilitates diagnostic purposes. The proposed approach improves the accuracy of anomaly detection and reduces false alarms. Simulations using the CMAPSS dataset demonstrate the model's efficacy in achieving timely anomaly detection, even in the case of an unbalanced dataset.

Bertrand Meyer

Software engineering concepts and processes are worthy of formal study; and yet we seldom formalize them. This "research ideas" article explores what a theory of software engineering could and should look like. Software engineering research has developed formal techniques of specification and verification as an application of mathematics to specify and verify systems addressing needs of various application domains. These domains usually do not include the domain of software engineering itself. It is, however, a rich domain with many processes and properties that cry for formalization and potential verification. This article outlines the structure of a possible theory of software engineering in the form of an object-oriented model, isolating abstractions corresponding to fundamental software concepts of project, milestone, code module, test and other staples of our field, and their mutual relationships. While the presentation is only a sketch of the full theory, it provides a set of guidelines for how a comprehensive and practical Theory of Software Engineering should (through an open-source community effort) be developed.

Fahim Hafiz, Md Jahidul Hoq Emon, Md Abid Hossain et al.

This paper proposes a novel curriculum for the microprocessors and microcontrollers laboratory course. The proposed curriculum blends structured laboratory experiments with an open-ended project phase, addressing complex engineering problems and activities. Microprocessors and microcontrollers are ubiquitous in modern technology, driving applications across diverse fields. To prepare future engineers for Industry 4.0, effective educational approaches are crucial. The proposed lab enables students to perform hands-on experiments using advanced microprocessors and microcontrollers while leveraging their acquired knowledge by working in teams to tackle self-defined complex engineering problems that utilize these devices and sensors, often used in the industry. Furthermore, this curriculum fosters multidisciplinary learning and equips students with problem-solving skills that can be applied in real-world scenarios. With recent technological advancements, traditional microprocessors and microcontrollers curricula often fail to capture the complexity of real-world applications. This curriculum addresses this critical gap by incorporating insights from experts in both industry and academia. It trains students with the necessary skills and knowledge to thrive in this rapidly evolving technological landscape, preparing them for success upon graduation. The curriculum integrates project-based learning, where students define complex engineering problems for themselves. This approach actively engages students, fostering a deeper understanding and enhancing their learning capabilities. Statistical analysis shows that the proposed curriculum significantly improves student learning outcomes, particularly in their ability to formulate and solve complex engineering problems, as well as engage in complex engineering activities.

Anastasia Lykova, Dmitriy Lobanov, Alexander Pankov et al.

This paper explores the effect of internal technological defects on the fatigue life of carbon fiber reinforced plastic (CFRP) under simple loading waveforms. One conducted experiments on CFRP specimens with embedded artificial defects, including delamination’s (circular dry-spot) and wrinkling. Following quasi-static tests, one developed a fatigue testing program using triangular and sine waveforms. The findings indicate that these simple waveforms do not significantly affect the fatigue resistance of defect-free CFRP or CFRP with internal technological defects. The presence of the wrinkling defect significantly diminishes the fatigue resistance of CFRP. However, constructing fatigue life curves in relative terms reveals that the reduction in fatigue properties is directly related to a decrease in strength properties. In the case of delamination (dry-spot) defects, a reduction in fatigue life by approximately 2.5 times was observed across the tested range.

Lei Huo, Qiang Li, Linlin Jiang et al.

Abstract Biodegradable porous Mg scaffolds are a promising approach to bone repair. In this work, 3D-spherical porous Mg–1.5Zn–0.2Ca (wt.%) scaffolds were prepared by vacuum infiltration casting technology, and MgF2 and fluorapatite coatings were designed to control the degradation behavior of Mg-based scaffolds. The results showed that the pores in Mg-based scaffolds were composed of the main spherical pores (450–600 μm) and interconnected pores (150–200 μm), and the porosity was up to 74.97%. Mg-based porous scaffolds exhibited sufficient mechanical properties with a compressive yield strength of about 4.04 MPa and elastic modulus of appropriately 0.23 GPa. Besides, both MgF2 coating and fluorapatite coating could effectively improve the corrosion resistance of porous Mg-based scaffolds. In conclusion, this research would provide data support and theoretical guidance for the application of biodegradable porous Mg-based scaffolds in bone tissue engineering. Graphical Abstract

Akiharu Esashi, Pawissanutt Lertpongrujikorn, Shinji Kato et al.

Function as a Service (FaaS) is poised to become the foundation of the next generation of cloud systems due to its inherent advantages in scalability, cost-efficiency, and ease of use. However, challenges such as the need for specialized knowledge, platform dependence, and difficulty in scalability in building functional workflows persist for cloud-native application developers. To overcome these challenges and mitigate the burden of developing FaaS-based applications, in this paper, we propose a mechanism called Action Engine, that makes use of tool-augmented large language models (LLMs) at its kernel to interpret human language queries and automates FaaS workflow generation, thereby, reducing the need for specialized expertise and manual design. Action Engine includes modules to identify relevant functions from the FaaS repository and seamlessly manage the data dependency between them, ensuring the developer's query is processed and resolved. Beyond that, Action Engine can execute the generated workflow by injecting the user-provided arguments. On another front, this work addresses a gap in tool-augmented LLM research via adopting an Automatic FaaS Workflow Generation perspective to systematically evaluate methodologies across four fundamental sub-processes. Through benchmarking various parameters, this research provides critical insights into streamlining workflow automation for real-world applications, specifically in the FaaS continuum. Our evaluations demonstrate that the Action Engine achieves comparable performance to the few-shot learning approach while maintaining platform- and language-agnosticism, thereby, mitigating provider-specific dependencies in workflow generation. We notice that Action Engine can unlock FaaS workflow generation for non-cloud-savvy developers and expedite the development cycles of cloud-native applications.

Yao Fu, Rameswar Panda, Xinyao Niu et al.

We study the continual pretraining recipe for scaling language models' context lengths to 128K, with a focus on data engineering. We hypothesize that long context modeling, in particular \textit{the ability to utilize information at arbitrary input locations}, is a capability that is mostly already acquired through large-scale pretraining, and that this capability can be readily extended to contexts substantially longer than seen during training~(e.g., 4K to 128K) through lightweight continual pretraining on appropriate data mixture. We investigate the \textit{quantity} and \textit{quality} of the data for continual pretraining: (1) for quantity, we show that 500 million to 5 billion tokens are enough to enable the model to retrieve information anywhere within the 128K context; (2) for quality, our results equally emphasize \textit{domain balance} and \textit{length upsampling}. Concretely, we find that naively upsampling longer data on certain domains like books, a common practice of existing work, gives suboptimal performance, and that a balanced domain mixture is important. We demonstrate that continual pretraining of the full model on 1B-5B tokens of such data is an effective and affordable strategy for scaling the context length of language models to 128K. Our recipe outperforms strong open-source long-context models and closes the gap to frontier models like GPT-4 128K.

Liping Li, Xuegang Liu, Yu Zhou et al.

Intelligent drilling has obtained a lot of attention in mining engineering, oil and gas production, and tunnelling engineering. The optimization of drilling parameters is one of the most important technologies of intelligent drilling while determining the key values to improve the drilling efficiency is still a difficulty. In this paper, we established a composite percussive rock breaking model of a full-size polycrystalline diamond compact (PDC) bit based on the continuous–discontinuous element method (CDEM). The evolution of rock fragmentation under the action of composite impact is analysed by the rock breaking volume and the torque applied on the drill bit during drilling. Based on actual construction, two key parameters, axial impact velocity and impact frequency, affecting the process of composite impact rock breaking were selected, to further investigate their effect on composite impact rock breaking. The fitting curves obtained from the sensitivity analysis of the rock breaking effect under different construction parameters were proposed to guide the intelligent drilling. Furthermore, the construction parameters of a diversion inclined shaft in the #2 construction branch hole of Tiantai Mountain pumped storage power station in Zhejiang Province were collected, which provides validation data for the proposed optimizing theory of the drilling parameters.

Ola Adel Ramadan Hemida, Hany Ahmed Abdalla, Hala Emad Elden Fouad

Abstract This research deals with the flexural performance of reinforced concrete beams which contain Recycled Concrete Aggregates (RCA) and were strengthened by Carbon Fiber Reinforced Polymers (CFRP). For this purpose, seven Reinforced Concrete (RC) beams were manufactured using RCA as a replacement of Normal Coarse aggregates (NCA) with percentages of (0%, 25%, 50%, and 100%). The cross-section of all beams was 150 × 300 mm and 2100 mm overall length and with loaded span of 1800 mm. Firstly four beams (group A) with different RCA ratios were loaded in a four-point loading configuration until failure. Secondly three beams (group B) were loaded to 30% of its ultimate load after that group B beams were strengthened using CFRP laminates on the lower face of the beams to be strengthened to resist flexural stress. Crack pattern, initial cracking load, ultimate load, mid-span deflection, and strain in main reinforcement were monitored. The results show that increasing RCA ratios generally leads to decreasing in the ultimate loads, for RCA ratios of 25%, 50% and 100% the decrease in beams ultimate load was with ratios 4.8%, 25.5% and 26.8%, respectively compared to control beam (0% RCA). The preloaded beams that were repaired with CFRP laminates have higher ultimate loads than beams without CFRP laminates and lower mid span deflection at maximum load (for instance repaired beam with 50% RCA ratio with CFRP laminate has shown higher ultimate load with 56.6% and less deflection with 36.9% compared to its corresponding unstrengthen beam).

Oleh Strelko

The history of bridge construction is an important part of historical knowledge. Developments in bridge construction technology reflect not only engineering advances, but also social, economic and cultural aspects of society. Engineers and scientists faced unique challenges when designing and building bridges depending on the technological level of the era, available materials and the needs of society. This process may reflect technological progress, changes in transportation needs, and cultural and social changes. The purpose of this article is to briefly review key moments and stages in the history of metal bridge construction using welding technology in the 20th century. The history of the development of the construction of metal bridges using welding goes back a little over 100 years. The short period from the construction of the first welded bridges to their first disasters led to the need to analyze the possible causes of these destructions. As the analysis performed showed, catastrophic destruction most often occurred under the influence of several factors, as well as a combination of external adverse influences and the internal “unpreparedness” of the structure for them. The above examples indicate that an irrational choice of steel could be both an independent cause causing brittle failure of structures, and an aggravating factor in the presence of structural violations, thermal stresses and welding defects. Over the years, bridge manufacturing technologies have been improved in different countries, and new steels and materials for their welding have been developed. Thanks to the use of carbon, low-alloy and alloy steel, designers abandoned the brutal “railroad-type” beam trusses and today metal bridges with graceful and beautiful silhouettes powerfully stride across the water surface, mountains and valleys. They became real attractions of megacities and country landscapes, and builders were able to successfully solve numerous technical and economic problems. An important contribution to the development of global bridge construction using welding technologies was made by the team of the Institute of Electric Welding of the Academy of Sciences of the Ukrainian SSR under the leadership of Academician Evgeny Oskarovych Paton. The team of the Institute of Electric Welding of the Academy of Sciences of the Ukrainian SSR, introducing welding into bridge construction, carefully checked the results and monitored the behavior of structures. A new grade of steel was created that was resistant to the formation of brittle and fatigue cracks, its welding technology was developed, a technology for installation welding of vertical sheets with forced formation of a seam was developed, and suitable welding materials were selected. At the time of construction in 1953, the Kyiv Evgeny Paton Bridge across the Dnipro River was the largest all-welded bridge in Europe, all seams of which, including assembly ones, were made for the first time using automatic and semi-automatic welding. In addition, the presence of large similar blocks in the design of the Evgeny Paton Bridge made it possible to mechanize assembly and welding operations and organize an in-line method for their production at the factory and installation, which improved the quality of welding work and reduced its labor intensity.

Azam Bozorgi, Masoud Mozafari, Mozafar Khazaei et al.

Introduction: Fabricating composite scaffolds with improved physicochemical properties as artificial microenvironments are of great interest in bone tissue engineering. Given advantageous properties of nano-hydroxyapatite/chitosan/gelatin (nHA/Cs/Gel) scaffolds, the present study aimed to synthesize a modified nHA/Cs/Gel biomimetic scaffold with improved features. Methods: Pure and copper (Cu)-substituted nHA was synthesized using the chemical precipitation method under controlled pH and temperature. Pure and Cu-substituted nHA/Cs/Gel scaffolds were fabricated by salt-leaching/freeze-drying method. Physicochemical characteristics of nanoparticles and scaffolds were explored using XRD, FTIR, FE-SEM/EDX, and ICP. Besides, scaffold mechanical strength, degradation, porosity, swelling, biomineralization, and cytocompatibility were assessed. Results: Pure and Cu-substituted nHA were synthesized and characterized with appropriate Cu substitution and improved physical properties. All scaffolds were highly porous (porosity >98%) and Cu incorporation reduced porosity from 99.555 ± 0.394% to 98.69 ± 0.80% while enlarged the pore size to more than100 µm. Cu-substitution improved the scaffold mechanical strength and the best result was observed in nHA.Cu5%/Cs/Gel scaffolds by the compressive strength 88.869 ± 19.574 MPa. Furthermore, 3% and 5% Cu-substituted nHA enhanced the scaffold structural stability and supported osteoblast spread, adhesion, survival, mineralization, and proliferation. Moreover, long-term and sustainable Cu release from scaffolds was observed within 28 days. Conclusion: Cu-substituted nHA/Cs/Gel scaffolds mimic the porous structure and mechanical strength of cancellous bone, along with prolonged degradation and Cu release, osteoblast attachment, viability, calcium deposition, and proliferation. Taken together, our results indicate the upgraded properties of nHA.Cu5%/Cs/Gel scaffolds for future applications in bone tissue engineering.

Lukáš Novák, Drahomír Novák

The paper is focused on probabilistic assessment and sensitivity analysis of existing prestressed concrete bridge using surrogate model in form of Polynomial Chaos Expansion (PCE). The bridge was selected in the framework of the European Project INTERREG AUSTRIA-CZECH REPUBLIC "TCZ190 SAFEBRIDGE" focused on advanced numerical analysis of existing bridges represented by non-linear finite element model. In this study, surrogate model in form of PCE was created, which represents very efficient type of surrogate model. One of significant advantages of PCE is powerful post-processing including sensitivity and moment analysis of the response, which is important part of probabilistic analysis. The obtained numerical results of advanced stochastic analysis consisting of uncertainty quantification and sensitivity analysis of the existing bridge structure are presented in the paper.

Eamon Whalen, Azariah Beyene, Caitlin Mueller

This paper introduces the Simulated Jet Engine Bracket Dataset (SimJEB): a new, public collection of crowdsourced mechanical brackets and accompanying structural simulations. SimJEB is applicable to a wide range of geometry processing tasks; the complexity of the shapes in SimJEB offer a challenge to automated geometry cleaning and meshing, while categorical labels and structural simulations facilitate classification and regression (i.e. engineering surrogate modeling). In contrast to existing shape collections, SimJEB's models are all designed for the same engineering function and thus have consistent structural loads and support conditions. On the other hand, SimJEB models are more complex, diverse, and realistic than the synthetically generated datasets commonly used in parametric surrogate model evaluation. The designs in SimJEB were derived from submissions to the GrabCAD Jet Engine Bracket Challenge: an open engineering design competition with over 700 hand-designed CAD entries from 320 designers representing 56 countries. Each model has been cleaned, categorized, meshed, and simulated with finite element analysis according to the original competition specifications. The result is a collection of 381 diverse, high-quality and application-focused designs for advancing geometric deep learning, engineering surrogate modeling, automated cleaning and related geometry processing tasks.